{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 基本信息\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame\n",
    "\n",
    "# 股票数据的读取\n",
    "import pandas_datareader as pdr\n",
    "\n",
    "# 可视化\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "# time\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = datetime(2015,9,20)\n",
    "alibaba = pdr.get_data_yahoo('BABA', start=start)\n",
    "amazon = pdr.get_data_yahoo('AMZN', start=start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "alibaba.to_csv('../homework/BABA.csv')\n",
    "amazon.to_csv('../homework/AMZN.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-09-21</th>\n",
       "      <td>65.379997</td>\n",
       "      <td>66.400002</td>\n",
       "      <td>62.959999</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22355100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-22</th>\n",
       "      <td>62.939999</td>\n",
       "      <td>63.270000</td>\n",
       "      <td>61.580002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>14897900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-23</th>\n",
       "      <td>61.959999</td>\n",
       "      <td>62.299999</td>\n",
       "      <td>59.680000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>22684600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-24</th>\n",
       "      <td>59.419998</td>\n",
       "      <td>60.340000</td>\n",
       "      <td>58.209999</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>20645700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-25</th>\n",
       "      <td>60.630001</td>\n",
       "      <td>60.840000</td>\n",
       "      <td>58.919998</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>17009100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close    Volume\n",
       "Date                                                                       \n",
       "2015-09-21  65.379997  66.400002  62.959999  63.900002  63.900002  22355100\n",
       "2015-09-22  62.939999  63.270000  61.580002  61.900002  61.900002  14897900\n",
       "2015-09-23  61.959999  62.299999  59.680000  60.000000  60.000000  22684600\n",
       "2015-09-24  59.419998  60.340000  58.209999  59.919998  59.919998  20645700\n",
       "2015-09-25  60.630001  60.840000  58.919998  59.240002  59.240002  17009100"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alibaba.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11d910588>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cPYHEOAtj81OZWJQRlFjF0OozqWutX1ZKFXXaZNJa+5olTUAqkAI0dNrHt/2I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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120d33710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['Adj Close'].plot(legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120ebcda0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wr2c2Fi2Dn4K1ZGuqj2Vti/iUEFb1z8btPU5FXoJbL5lKB3dhiWKtkxfX7nR8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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120ec3a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['Volume'].plot(legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120ee9a90>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gdmOMscwfvdLVaXNy3bSr+518FkKMXUlb6Lv9PbT7OyhJLWJGzjSmZ0/ttz7P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\nc805lI7LGjSfYZ7gq0O8NDZ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      "text/plain": [
       "<matplotlib.figure.Figure at 0x120fb3b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['Adj Close'].plot()\n",
    "amazon['Adj Close'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-09-21</th>\n",
       "      <td>65.379997</td>\n",
       "      <td>66.400002</td>\n",
       "      <td>62.959999</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22355100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-22</th>\n",
       "      <td>62.939999</td>\n",
       "      <td>63.270000</td>\n",
       "      <td>61.580002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>14897900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-23</th>\n",
       "      <td>61.959999</td>\n",
       "      <td>62.299999</td>\n",
       "      <td>59.680000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>22684600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-24</th>\n",
       "      <td>59.419998</td>\n",
       "      <td>60.340000</td>\n",
       "      <td>58.209999</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>20645700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-25</th>\n",
       "      <td>60.630001</td>\n",
       "      <td>60.840000</td>\n",
       "      <td>58.919998</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>17009100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close    Volume\n",
       "Date                                                                       \n",
       "2015-09-21  65.379997  66.400002  62.959999  63.900002  63.900002  22355100\n",
       "2015-09-22  62.939999  63.270000  61.580002  61.900002  61.900002  14897900\n",
       "2015-09-23  61.959999  62.299999  59.680000  60.000000  60.000000  22684600\n",
       "2015-09-24  59.419998  60.340000  58.209999  59.919998  59.919998  20645700\n",
       "2015-09-25  60.630001  60.840000  58.919998  59.240002  59.240002  17009100"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alibaba.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "alibaba['high-low'] = alibaba['High'] - alibaba['Low']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>high-low</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-09-21</th>\n",
       "      <td>65.379997</td>\n",
       "      <td>66.400002</td>\n",
       "      <td>62.959999</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22355100</td>\n",
       "      <td>3.440003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-22</th>\n",
       "      <td>62.939999</td>\n",
       "      <td>63.270000</td>\n",
       "      <td>61.580002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>61.900002</td>\n",
       "      <td>14897900</td>\n",
       "      <td>1.689998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-23</th>\n",
       "      <td>61.959999</td>\n",
       "      <td>62.299999</td>\n",
       "      <td>59.680000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>22684600</td>\n",
       "      <td>2.619999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-24</th>\n",
       "      <td>59.419998</td>\n",
       "      <td>60.340000</td>\n",
       "      <td>58.209999</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>59.919998</td>\n",
       "      <td>20645700</td>\n",
       "      <td>2.130001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-25</th>\n",
       "      <td>60.630001</td>\n",
       "      <td>60.840000</td>\n",
       "      <td>58.919998</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>59.240002</td>\n",
       "      <td>17009100</td>\n",
       "      <td>1.920002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close    Volume  \\\n",
       "Date                                                                          \n",
       "2015-09-21  65.379997  66.400002  62.959999  63.900002  63.900002  22355100   \n",
       "2015-09-22  62.939999  63.270000  61.580002  61.900002  61.900002  14897900   \n",
       "2015-09-23  61.959999  62.299999  59.680000  60.000000  60.000000  22684600   \n",
       "2015-09-24  59.419998  60.340000  58.209999  59.919998  59.919998  20645700   \n",
       "2015-09-25  60.630001  60.840000  58.919998  59.240002  59.240002  17009100   \n",
       "\n",
       "            high-low  \n",
       "Date                  \n",
       "2015-09-21  3.440003  \n",
       "2015-09-22  1.689998  \n",
       "2015-09-23  2.619999  \n",
       "2015-09-24  2.130001  \n",
       "2015-09-25  1.920002  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alibaba.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x120fdcf98>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qLdUttz+8Cd/49Wps2uGdysNvPnBN07Dn4GDe8ykVoMCdfwuCD1yU7+4ntqB3YAx/fnxL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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120ff32e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['high-low'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# daily return\n",
    "alibaba['daily-return'] = alibaba['Adj Close'].pct_change() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x121504d68>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5kmmcO7Mw5JhYzqR2+0dLazcamJ3Hw6Nt7T7sg/UdlgJoVnoyn71qXtTniFfQ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\nMV0Yqoe/MaV/CHdqDp+JCaLliBGOlv1ev+3irWa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bythc+0JzhrKSn59JUVEOO4808pQe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\nj0MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x121576978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['daily-return'].plot(figsize=(10,4),linestyle='--',marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12169c630>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kcEFmro2Is4HjykmeBczPzPkR8Rbgk8DPy3HnZ+bNNebqAf4HuL+c7I7MPKc8iurSctr1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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1215762b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alibaba['daily-return'].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x121b15f98>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x121c6ba20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(alibaba['daily-return'].dropna(),bins=100,color='purple')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
